BetaShared delivers improved prediction models and better insights from collaborative data sharing.
BetaShared aggregates anonymised data from collaborators—whether teams within an organisation or different organisations that wish to share data. Using our advanced compute platform, we train state-of-the-art models on this aggregated information. Collaborators then receive parameters derived from these models—trained on significantly larger data sets—to update their local models, ensuring enhanced performance.
How it works
Unified Data Aggregation and Enhanced Model Training
Data is anonymised using BetaShared’s standardised protocol.
We aggregate the anonymised data from collaborators—whether teams within an organisation or different organisations that wish to share data.
Using our advanced compute platform, we train state-of-the-art models on this aggregated information.
Collaborators then receive parameters derived from these models—trained on significantly larger data sets—to update their local models, ensuring enhanced performance.
Versatile Data Integration Across Collaborative Scenarios
Our platform is engineered to seamlessly integrate data from diverse collaboration scenarios. It efficiently aggregates information whether it’s a single collaborator with multiple responses from identical or varied environments, or multiple collaborators bringing in data with varying response and variable patterns. From identical responses with the same variables to distinct responses with overlapping variables, our system is designed for comprehensive data harmonisation and interlinking.